code: def __init__(
      self,
      k_at_hops,
      num_adjacent_linkages,
      node_geo_feat_len,
      pooling_scale,
      pooling_output_size,
      nms_thr,
      min_width,
      max_width,
      comp_shrink_ratio,
      comp_w_h_ratio,
      comp_score_thr,
      text_region_thr,
      center_region_thr,
      center_region_area_thr,
  ):
      assert len(k_at_hops) == 2
      assert isinstance(k_at_hops, tuple)
      assert isinstance(num_adjacent_linkages, int)
      assert isinstance(node_geo_feat_len, int)
      assert isinstance(pooling_scale, float)
      assert isinstance(pooling_output_size, tuple)
      assert isinstance(nms_thr, float)
      assert isinstance(min_width, float)
      assert isinstance(max_width, float)
      assert isinstance(comp_shrink_ratio, float)
      assert isinstance(comp_w_h_ratio, float)
      assert isinstance(comp_score_thr, float)
      assert isinstance(text_region_thr, float)
      assert isinstance(center_region_thr, float)
      assert isinstance(center_region_area_thr, int)
  
      self.k_at_hops = k_at_hops
      self.active_connection = num_adjacent_linkages
      self.local_graph_depth = len(self.k_at_hops)
      self.node_geo_feat_dim = node_geo_feat_len
      self.pooling = RoIAlignRotated(pooling_output_size, pooling_scale)
      self.nms_thr = nms_thr
      self.min_width = min_width
      self.max_width = max_width
      self.comp_shrink_ratio = comp_shrink_ratio
      self.comp_w_h_ratio = comp_w_h_ratio
      self.comp_score_thr = comp_score_thr
      self.text_region_thr = text_region_thr
      self.center_region_thr = center_region_thr
      self.center_region_area_thr = center_region_area_thr
  
file_path: PaddleOCR/ppocr/modeling/heads/proposal_local_graph.py
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import cv2
  import numpy
  import paddle
  import paddle.nn
  import paddle.nn.functional
  from lanms import merge_quadrangle_n9
  from ppocr.ext_op import RoIAlignRotated
  from .local_graph import euclidean_distance_matrix, feature_embedding, normalize_adjacent_matrix
label_desc: Use image node_id 1 to create a new ProposalLocalGraphs object  with example: obj = ProposalLocalGraphs(k_at_hops, num_adjacent_linkages, node_geo_feat_len, pooling_scale, pooling_output_size, nms_thr, min_width, max_width, comp_shrink_ratio, comp_w_h_ratio, comp_score_thr, text_region_thr, center_region_thr, center_region_area_thr)